Natural language content in ontologies is crucial to any human interaction with them, but scarcely available. Terminology science centers on best practices in domain-specic natural languages. Hence, ontologies can benet from the systematic approach of terminology to natural language denitions. This paper proposes an Annotation Ontology Design Pattern named Natural Language Denition ODP that provides natural language denitions for ontology classes. For this purpose, a (semi-)automated method for implementing this pattern combining ontology verbalization and information extraction is investigated herein and exemplied in the domain of nance.
A growing number of application scenarios for Semantic Web (SW) ontologies
render reusable, high-quality solutions to their design increasingly important.
For this purpose, Ontology Design Patterns (ODP) dene a formal methodology
for various aspects of ontological design, ranging from Logical to Presentation
ODPs [
Ever since its advent, terminology science has realized the need of providing a systematic approach to NL denitions. Concept-centered terminologies as dened by ISO 704:2009 and 1087:2000 consist of sets of terminology concepts in specialized domains. NL denitions are required to form these terminology concepts and their interrelations. In contrast, ontology concepts are formally dened by means of logics. Combining the formal ontological denition with the terminological NL denition authoring method results in a multidimensional approach formalized as the proposed Annotation ODP. Thereby, the ISO 704 method of combining the denomination of the superordinate concept with (a) characteristic(s), delimiting the concept to be dened from its related concepts, can be (semi-) automated and is the foundation of the proposed pattern. Given domain-specic, axiomatized ontology elements with a minimum of NL coverage in labels or fragment identiers, the superordinate concept’s denomination can be identied and applied by using its subsumption hierarchy. For the non-trivial purpose of obtaining characteristics, three mutually complementing approaches are proposed: ontology verbalization, utilizing existing NL content, and information extraction. An example is provided by applying the pattern to the partially available NL content of Fadyart’s Finance Ontology 1. 2
The objective of the NL Denition ODP is to dene an ontology concept in natural language(s). Ontologies represent knowledge by formalizing vocabularies of terms as well as their interrelations and dene their meaning formally. Terminologies mostly rely on NL characteristics to establish NL denitions for concepts and interrelate concepts designated by terms, appellations, or symbols. The two most important types of denitions as specied by ISO 704 are extensional denitions, listing the instances of a concept, and intensional denitions. The latter constitutes a combination of superordinate concept and manually identied delimiting characteristic(s) for concepts related generically.
The intensional approach oers the most explicit, consistent, and precise method to denition formation. It is intended to provide the minimum of information needed for human users to dierentiate one terminology concept from another. To facilitate its automation, the basic textual description of ISO has been adopted and formalized for proposing the NL Denition ODP introduced in Denition 1 and illustrated in Example 1.
The pattern denes the NL denition of an entry term, which corresponds to the label of the ontology class. The singular form of the term is preferred, unless only available in plural, e.g. liabilities. It utilizes the label or fragment identier of the superordinate concept, which for the experiment herein is restricted to Noun Phrases (NP). Thereby, it obtains a context and implicitly inherits the characteristics of the superclass. The NP is connected to characteristics by utilizing a nite set of relative pronouns, verbs, and where applicable verbalized object properties. The same elements and a coordinating conjunction are needed to string together several characteristics.
Obtaining the characteristic(s) relies on a three-tiered mutually complementing approach of ontology verbalization, utilizing existing NL content, and infor
mation extraction from structured Web resources. All three of them help specifying the relative pronoun and linking verb to be used for the concept to be dened. Denition 1: NL Denition ODP Entry Term [A/An] NP<superclass> [which/that/who/whose] [(can) be/include/belong to/classify as OR <objectProperty>] [(<characteristic(s)>) and] <characteristic> Example 1: NL Denition of Concept Card (Fadyart Finance Ontology) Card [A] payment instrument [that] [has as card type] <a credit card or debit card> and [has as card data] <a start date, sequence number, holder name, expiry date, issuer name, card number, security code>
Ontology verbalization refers to the translation of ontology concepts,
relations, and axioms to (controlled) natural languages, such as Attempto Controlled
English [
In a next step, the existing rdfs:comment of the ontology class is linked to the NP and, where applicable, verbalized content by means of a coordinating conjunction and the identied relative pronoun, which, if not available in the comment, can be obtained from Wiktionary.
If no NL content is available, re-using existing structured Web resources, such as DBpedia, has been considered. The tentative information extraction process herein relies on string matching and an immediate subsumption to top DBpedia ontology concepts (e.g. Organization, Resource). Reducing NL denitions to DBpedia information might result in quality issues. For instance, circular denitions are frequent on DBpedia, i.e., a term is dened by itself or by a second term that refers back to the rst term. For instance, Debtor is dened as Debtor owes a debt to someone .... Applying the proposed pattern ensures the proper context for the concept, i.e., superordinate concept, and DBpedia information provide useful additional details.
Due to its systematic nature, the described pattern enables a consistent formation of NL denitions, which strongly enhances the human readability of ontologies it is applied to. The proposed pattern is illustrated for the English language and requires minor adaptations for its realization in other NLs syntactically similar to English provided lexical resources are available.
An OWL ontology serves as the input to the intended system design, here exemplied with Fadyart’s Finance Ontology in English. By means of the OWL API the ontology can be parsed, the subclass relations and object properties identied, and an annotation property can be added. Starting from >, the subsumption hierarchy is traversed to the rst concept not directly subsumed by it. If its superordinate concept contains no label, its fragment identier is tokenized (using e.g. the Stanford Core NLP) and represents the NP<superclass> of Denition 1. In Example 2, the class ClientPortfolio is the subclass of AccountsPayable.
To ensure the correct grammatical number and relative pronoun, the superclass term is queried in Wiktionary, e.g. Java-based Wiktionary Library 2. Here, the query returns plural only and the relative pronoun that 3 for Accounts Payable. Subsequently, tokenization and verbalization pattern P4 dened in the previous section are applied to the object property of Example 2. Its range consists of a union of three classes, which is verbalized using pattern P1. Finally, the existing comment is to be added to the already obtained denition. By means of Wiktionary Clients in the existing rdfs:comment is identied as countable noun, so its singular form can be combined with the obtained denition using a coordinating conjunction and the relative pronoun identied above. The derived denition can be added to the concept ClientPortfolio as rdfs:comment . Example 2: Class ClientPortfolio in Manchester Syntax Original Input in OWL Ontology: <http://www.fadyart.com/Finance.owl> ...
ObjectProperty: hasClientPortfolioBenecialOwnerOfIncome
SubPropertyOf: hasAccountDomain Domain: ClientPortfolio Range: PartyHolder or PartyLegalRepresentative or
PartyUsufructuary Class: AccountsPayable
Annotations: rdfs: label "Accounts payable"@en
SubClassOf: ShortTermLiabilities Class: ClientPortfolio
Annotations: rdfs: label "Client accounts"@en, rdfs :comment "The clients of the nancial institution for who’s account the securities handling operations are performed."^^ xsd:string SubClassOf: AccountsPayable Resulting Denition
Client Account Accounts payable that has as client lpeoarsttfoolinoe pbaernteycihaolldoewr,nepraortfyinlceogmale at representative , or party usufructuary and tihnasttitiustiaonclifeonrt wohfo’tsheaccnoaunnctiatlhe securities handling operations are performed.
Several object properties and enormous unions render it necessary that domain experts decide which verbalization most adequately denes the concept. Additionally, at times comments are utilized for supplementary information rather than NL denitions of concepts, which is why for some cases the comments might not be re-used for the denition formation process. 4
Glosses for ontology concepts reuse existing lexical resources, e.g. WordNet, to
provide ontology engineers with various linguistic descriptions to choose from for
a specic concept [
linguistic descriptions (e.g. lemon 4) either re-use glosses for NL descriptions or
derive meaning by pointing to the semantic object in the ontology. Ontology
verbalization utilizes formalized knowledge in ontologies to derive NL descriptions.
For instance, the SWAT project 5 facilitates the understandability of verbalized
entailments by providing individual inference steps in the English language [
This paper proposes a NL denition ODP on the basis of denition formation methods from terminology science. Subsequent to dening the pattern, a (semi-)automated design to obtaining NL denitions by means of ontology verbalization, utilization of existing NL comments, and information extraction has been exemplied in the nancial domain. In terms of future work, the degree to which the pattern can be generalized to other domains will be tested. As regards, information extraction, a profound disambiguation process will be considered. Furthermore, its formalization for a submission to the ontology design pattern repository is planned.
5 http://swatproject.org